Project #4: Experimental Testing of Allocation of Multiple UAVs Tim Arnett, Aerospace Engineering,...

Project #4: Experimental Testing of Allocation of Multiple UAVs

Tim Arnett, Aerospace Engineering, Junior, University of Cincinnati

Devon Riddle, Aerospace Engineering, Junior University of Cincinnati

ASSISTED BY:

Chelsea Sabo, Graduate Research Assistant

Dr. Kelly Cohen, Faculty Mentor

Motivation & Operational Goals of Experimental Testing

• Search and Rescue• Weather Observation• Forest Fire Monitoring

• Traffic Surveillance• Border Patrol• Military

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Project Goals

• Learn to interface with hardware for controller development

• Understand the benefits and disadvantages of using different routing algorithms for UAVs

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Objectives• Objective 1: Interface with cooperative control

development hardware– Interface and run algorithms on AR Drones– Interface and run algorithms on AMASE

• Objective 2: Validate task allocation algorithm both in simulation and experimentally

• Objective 3: Test and compare cooperative control strategies for UAVs

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Experimental Setup

• AR Drone• OptiTrack System• Software Interface• Waypoint Following Algorithm

– PID Control– Fuzzy Logic Control– Potential-based Control

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Experimental Setup

• AR Drone– Commercially available quadrotor– Can be controlled by a device using wireless

network adapter

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Experimental Setup

• Optitrack System– Cameras provide real time position data– Data can be imported into MatLab

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Experimental Setup

• Software Interface– PC client with wireless capability– Wireless router to connect to multiple drones

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Experimental Setup

• Waypoint Following Algorithm– PID Control– Fuzzy Logic Control– Potential-based Control

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U x

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Communication Pathway10

Command Value Conversion

AR Drone requires commands in text strings with values formatted as a 32-bit signed integer• Command string example

– CMD = sprintf('AT*PCMD=%d,%d,%d,%d,%d,%d\r',i,1,0,1036831949,0,0);

– fprintf(ARc, CMD)– Arguments in order are sequence, flag, roll,

pitch, ascent rate, and yaw rate

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AMASE

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Basic Overview• A simulation program.

– Sets up scenarios– Runs the main simulation that is wanted – Has the capabilities of analyzing the results

as the simulation is run.

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Important Features

• The Map• Direct XML-editing (extensible markup language)• The Event Editor

– The features mentioned above are the three basic methods use for entering information into a scenario to simulate it.

• Multi Flight• CMASI

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The Map XML Editing

Event Editor

Create Scenario

Plan Request (CMASI)

Validation

CMASI

• Common Mission Automation Services Interface– A system of interactive objects that pertain to

the command and control of a UAV system. • Communicate with the components

– LMCP

– Defines data types and enumerations.

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TimelineWeek 1

Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10

Research

Learn AMASE

Test Control Algorithm

Analyze Control Algorithm

Validation

Final Report

Journal Paper Due Final Day

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Conclusions18

• Challenges– Modeling the system for controller– Communicating with drone(s)

Questions?19